with Larry Li

Hello. My name is Larry Lee, a system engineer for Texas Instruments 3D time of flight sensors. In this video, I will demonstrate how TI 3D time of flight solution can be used for obstacle detection, collision avoidance, and navigation. TI 3D time of flight sensors work by illuminating the scene with modulated light and measuring the phase delay of the returned light. The phase delay is proportional to the actual distance.
Every pixel in the TI solutions perform this measurement in parallel, resulting in depth map. The amplitude of the returned light is also measured, resulting in an amplitude map. The depth map and the amplitude maps, together with knowledge of the lens used, can be used to compute a point cloud, a collection of xyz data points in space. Knowing the distance of every point in the scene can help robots understand its surroundings. In fact, 3D time of flight sensor is well-suited for machine vision for a variety of mobile robot applications. Solving key care about, such as collision detection, maps, base navigation, self docking, multi-robot operation.
3D time of sensors works perfectly well in the dark due to self illumination. Let's take a look at a collision avoidance example. In this video clip, we will see a mobile robot equipped with TI time of flight sensor detecting obstacles and slowing down using relatively simple algorithm. First, the robot to tax obstacles by finding the nearest point in the field of view. If the shortest distance is closer than the threshold, the robot will slow down and eventually comes to a stop. Once stopped to continue without collision, the robot must decide which way to turn. The decision depends on which direction will lead to a more wide open space, is to divide the depth image into a left and right halves, and add the pixel depth of each. Whichever half's having the larger sum is the direction to turn. Here is an example of robot approaching a wall at an angle using this approach.
Furthermore, some obstacles can be small or thin, difficult to see with a single pixel range sensor. Consider shoelaces, wires, and tables that can jam up a vacuum cleaner robot, or thin chair legs that robot may have to vacuum around. TI offers time of flight solutions in both 320 by 240 and 80 by 60 resolutions to support different requirements. For navigating indoor where GPS doesn't work, the 3D time of flight sensor can help a robot build a map of his environment and locate itself in it. Having a map will enable the robot to plan its path and navigate more safely and efficiently.
Here is a robot equipped with TI 3D time of flight sensor, building up a map as it moves about the house. The map is at the bottom right.
Thank you for watching this video demo. If you'd like to learn more about TI 3D time of flight solutions, please contact your local sales representatives or distributor for pricing and availability. For any general sales questions, you can send them to support@ti.com. For technical information, visit the TI 3D time of flight page, or check out the E2E forum for optical sensors. Finally, for software development, check out [INAUDIBLE] on github.com. 大家好！ 我叫 Larry Lee， 是来自德州仪器 (TI) 的 3D 飞行时间传感器的系统工程师。 在本视频中，我 将演示 TI 3D 飞行时间 解决方案如何 可用于障碍物 检测、避碰 和导航。 TI 3D 飞行时间传感器的 工作方式为， 利用调制光 点亮场景 并测量返回光的 相位延迟。 相位延迟与实际 距离成比例。 TI 解决方案中的 每个像素都可并行 执行这种测量，最终得到 深度图。 此外，还会测量 返回光的 振幅，这样会 得到振幅图。 深度图和 振幅图 加上一些所用镜头的 知识一起 可用于计算点云， 即空间中的一组 xyz 数据点。 了解场景中 每个点的距离 可帮助机器人理解 其周围的环境。 实际上，3D 飞行 时间传感器 非常适合各种 移动机器人应用的 机器视觉。 我们关心的几个关键问题是 碰撞检测、地图、 基本导航、自动对接和 多机器人操作。 由于 3D 飞行时间传感器的 自我照明功能， 它可在黑暗中完美 工作。 让我们看一个 避碰示例。 在此视频剪辑中，我们将 看到一个配有 TI 飞行时间传感器的移动机器人 利用相对简单的算法来 检测障碍物并 减速。 首先，要碰到 障碍物的机器人 会寻找视野 中最近的点。 如果最短距离 比阈值近， 机器人会减速并 最终停下来。 一旦停止继续操作 而没有发生碰撞， 机器人必须决定 转向哪条路。 决定取决于 哪个方向 会通向 更宽敞的空间， 这需要将深度图 划分为左右两半， 并为每一边添加像素深度。 总和较大的 一边 即为要转至的方向。 这里是一个机器人利用这种 方法以一定角度接近 墙面的示例。 此外，有些障碍物 可能很小或很细薄， 难以使用 单像素范围的传感器看到。 考虑一下可能堵塞 真空吸尘器 机器人的鞋带、电线 和桌子， 或者机器人可能必须对其 周围进行清理的细椅子腿。 TI 提供的飞行时间 解决方案 同时支持 320 × 240 和 80 × 60 分辨率， 可满足不同的 需求。 要在 GPS 不工作的 室内进行导航， 3D 飞行时间 传感器可以帮助 机器人构建 其所处环境的地图 并在其中自我定位。 拥有地图将使 机器人能够规划其路径 并且更安全 而有效的进行导航。 这里是一个配有 TI 3D 飞行时间传感器的机器人， 它在房间中 移动时构建了一张地图。 地图位于右下角。 感谢您观看 本视频演示。 如果您希望 了解关于 TI 3D 飞行时间 解决方案的更多信息，请与您 当地的销售代表 或分销商联系来获取 定价和供货情况。 关于任何一般 销售问题，您 可以将问题发送至 support@ti.com。 有关技术问题，请访问 TI 3D 飞行时间页面 或查阅 E2E 论坛来了解关于光学传感器的信息。 最后，关于 软件开发， 请查阅 github.com 上的 VoxelSDK。

Details

Date:
September 13, 2016

Autonomous navigation and collision avoidance are critical functions for safety and efficient operation in both consumer and industrial robots. Learn about how 3D time-of-flight sensors enable two different robots to “see” their environment and move around without collision.

In the first part of the video, a vacuum robot equipped with relatively simple algorithms and a depth image from the 3D time-of-flight sensor is able to determine when to slow down, when to stop, which direction to turn, and how to maneuver around obstacles without collision. The second half of the video demonstrates a home robot equipped with the same 3D time-of-flight sensor and more advanced algorithms. This robot builds a map of the environment and uses the map to plan its path.